Effect of Implementation Intentions to Change Behaviour: Moderation by Intention Stability
Bibliographic record
Abstract
The aim of this study was to assess the effects of implementation intentions on leisure-time physical activity, taking into account the stability of intention. At baseline (T0), 349 participants completed a psychosocial questionnaire and were randomly assigned to implementation intention or control condition. Three months after baseline assessment (T1), participants in the experimental group were asked to plan where, when, and how they would exercise. Leisure-time physical activity was assessed 3 mo. later (i.e., at 6-mo. follow-up; T2). The intervention had no significant effect on physical activity at 6-mo. follow-up. However, a significant interaction of group and intention stability was observed, with the effect of the intervention on behaviour statistically significant only among those with unstable intention. Intention stability thus moderated the effect of the intervention, i.e., the intervention was more successful among individuals who needed support to change (unstable intenders).
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.012 | 0.043 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".